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<title>Algorithm types</title>

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  <p><b>ALGORITHM TYPES</b></p>

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<p>There exists several types of algorithms according to their functionality. Let us 

see as they are:</p>

<ul>

  <li><b>Pre-process:</b> they are discretization algorithms, instances selection and features selection. 

    As their name suggests, they are used to add a pre-processing step over the initial 

    data set, before applying a knowledge extraction algorithm.<br><br>
		<p align="center"><img src="imag/exp_algoPre.jpg"></p><br>

  </li>

  <li><b>Methods:</b> they are knowledge extraction algorithms: decision tree and rule extraction in supervised 

    learning, neural networks, unsupervised learning, etc...<br><br>
		<p align="center"><img src="imag/exp_algoMet.jpg"></p><br>

  </li>

  <li><b>Post-process:</b> they are algorithms that are inserted in final steps in order to refine the results 

    obtained by the previous algorithms.<br><br>
		<p align="center"><img src="imag/exp_algoPost.jpg"></p><br>

  </li>

  <li><b>Test:</b> they are statistical algorithms to analyze the results obtained by the previous methods.<br><br>
	<p align="center"><img src="imag/exp_algoTest.jpg"></p><br>

  </li>

  <li><b>Results:</b> they are features to show the results obtained by the previous methods.<br><br>
	<p align="center"><img src="imag/exp_results.jpg"></p>

  </li>


</ul>

<p>Within these types, the algorithms are classified according to the 

  family to whom they belong. These families appear in the drop-down tree, allowing the 

  navigation through the different algorithms until finding the one the user is interested in, as we can see in the above pictures. </p>
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